جست‌وجوی استاد و پژوهشگر

Cristian De Gobbaمشاهده پروفایل

پژوهشگر

• Analytical Chemistry
• Food Science
• Biochemistry
• +۴ مورد دیگر

Cristian De Gobba is a PhD Guest researcher at the Department of Nutrition, Exercise and Sports within the Faculty of Science at the University of Copenhagen. His research focuses on developing analytical methods for food and nutrition science using advanced chromatography and mass spectrometry techniques. Dr. De Gobba's primary research interests include analytical chemistry methods development, particularly for the study of advanced glycation end-products (AGEs), alcohol biomarkers, and Maillard reaction products. His expertise spans food science, nutrition, and biochemistry, with specific technical skills in LC-MS, HPLC, and protein characterization techniques. He has developed methods for extraction and quantification of various compounds from food systems and biological samples, including alcohol metabolites in hair and acetaldehyde adducts in hemoglobin. His recent research demonstrates a strong focus on protein chemistry in food systems, particularly milk proteins and their digestion patterns, as well as the analysis of bioactive compounds in various food matrices. His work often involves collaboration with industry partners such as Danish Crown Ingredients and focuses on practical applications in food production and nutrition. The publications show consistent work in method development for analyzing complex food components and their effects on human health. Dr. De Gobba has extensive experience with protein and peptide identification using LC-MS/MS, SEC-HPLC, and UV-Vis spectroscopy. His work includes characterizing blood hydrolysates for edible protein powders and identifying bioactive peptides from milk proteins. He has developed novel methods for simultaneous determination of multiple AGEs and quantification of thiol quinones adducts.

Stevin Gehrkeمشاهده پروفایل

استاد

• Biomimetic Materials
• Hydrogels
• Tissue Engineering
• +۵ مورد دیگر

Dr. Stevin Gehrke is a Professor in the Department of Chemical and Petroleum Engineering at the University of Kansas , where he leads the KU Hydrogel Lab . His research focuses on hydrogels , biomimetic materials , and biomedical applications , with expertise in drug delivery , tissue engineering , and protein-based biomaterials . Education: B.S. in Chemical Engineering, Kansas State University M.S. and Ph.D. in Chemical Engineering, University of Minnesota Research Themes: Environmentally responsive hydrogels for pharmaceutical and biotechnology applications Biosynthesis of artificial proteins for tissue engineering via genetic engineering Advanced polymer characterization techniques (NMR, QCM-D, rheology) Biomechanical studies of insect cuticle for bioinspired material design Development of novel hydrogel coatings for medical devices Publication Trends: Recent work emphasizes biomimetic hydrogel design for cartilage regeneration Key innovations in nanoparticle-reinforced hydrogels and 3D bioprinting Long-standing contributions to responsive hydrogel kinetics and protein separation techniques Labs & Collaborations: Directs the KU Hydrogel Lab for advanced biomaterials research Collaborates with agricultural, medical, and international institutions (Sweden, Japan, Brazil)

Joerg Lahannمشاهده پروفایل

استاد

• Drug Delivery
• Gene Therapy
• Biomaterials
• +۷ مورد دیگر

Joerg Lahann is a Professor at the University of Michigan with appointments in Chemical Engineering , Materials Science and Engineering , Macromolecular Science and Engineering , and Biomedical Engineering . He serves as Director of the Academic Program Biointerfaces Center and is affiliated with multiple research institutes including the Weil Institute for Critical Care Research , Rogel Cancer Center , and Biosciences Initiative . PhD in Macromolecular Chemistry from Rheinisch-Westfälische Technische Hochschule Aachen (1998) Dr. Lahann's research spans biotechnology , nanoparticle engineering , and surface chemistry , focusing on drug/gene delivery systems , advanced biomaterials , and chemical vapor deposition for engineered surfaces. His work addresses challenges in oral cancer chemoprevention , neuro-oncology , and synthetic biology applications . Recent publications highlight innovations in protein nanoparticle design for targeted therapies , deep learning-based surface analysis , and liquid crystal-templated polymerization . His team has made significant advances in non-viral gene delivery , biofilm disruption , and smart biomaterials for dental applications . University of Michigan Biointerfaces Institute Innovation Fellowship (2023) Dr. Lahann supervises research in nanoparticle engineering , biomaterials , and chemical manufacturing processes . His lab has received substantial funding from NSF , NIH , and industry partners for projects including 3D scaffold development , biocontainment strategies , and advanced manufacturing techniques . The Lahann Lab at the Biointerfaces Institute (Ann Arbor, MI) develops therapeutic nanoparticles , engineered extracellular matrices , and multifunctional coatings with applications in cancer therapy , regenerative medicine , and oral disease prevention .

Martin Sahlénمشاهده پروفایل

دانشیار

• astrophysics
• astronomy
• cosmology
• +۹ مورد دیگر

Martin Sahlén is an Associate Professor in the Department of Physics and Astronomy at Uppsala University, specializing in astronomy with a focus on astrophysics. His research spans theoretical and observational studies of the large-scale structure of the universe through galaxy clusters, voids, and the universe's first galaxies to understand galaxy physics, star formation, dark energy, dark matter, cosmic inflation, and the reionization process in the early universe. Dr. Sahlén's research interests center on cosmology, particularly the intersection of theoretical models and observational data. He employs Bayesian inference techniques to analyze cosmological datasets, with special attention to the philosophy of cosmology, including model inference, fine-tuning of natural constants, and multiverse explanations. His work bridges observational astronomy with theoretical physics to address fundamental questions about the universe's structure and evolution. His recent publications (2024-2025) predominantly focus on the Euclid space mission, representing a major portion of his scholarly output. These works span instrumentation, data analysis techniques, cosmological simulations, and theoretical interpretations. Key themes include constraints on modified gravity models, galaxy cluster analyses, weak lensing studies, and machine learning applications for extracting physical parameters from astronomical data. His research demonstrates a consistent focus on leveraging next-generation observational data to test fundamental cosmological theories. Dr. Sahlén serves as Principal Investigator for multiple significant research grants, including: (1) 'The Galaxy – Dark Matter Connection with HST, JWST and EUCLID' (2021-2026, 8 MSEK); (2) 'Searching for New Physics in the Early Universe' (2022-2024, 1 MSEK); and (3) 'Astronomical object classification and anomaly detection with complex spectroscopic 4MOST data sets' (2023-2027, 4 MSEK). He actively participates in major scientific collaborations including 4MOST, BUFFALO, Euclid and SKA Observatory, and contributes externally to the Dark Energy Survey. As an educator, Dr. Sahlén is responsible for and teaches the interdisciplinary course 'Three Approaches to Cosmology' (10 credits), which likely reflects his broad expertise spanning observational, theoretical, and philosophical aspects of cosmology.

• Algebra
• Computer Science
• Polynomial Identities
• +۳ مورد دیگر

Francesca Saviella Benanti is a researcher in the Department of Mathematics and Computer Science at the University of Palermo. Her teaching activities include Algebra 1 for Mathematics degree programs and laboratory courses in mathematics education. Research Interests Polynomial identities in noncommutative algebras Graded algebras and involution structures Asymptotic behavior of Hair polynomials Capelli identities and their applications Trace algebras for matrix structures Cryptography and algorithmic security Publications Overview Her research over two decades focuses on polynomial identities, matrix algebras, and their asymptotics, with recent work on graded varieties and central exponents. Projects and Initiatives PNRR Laboratory "Mathematics of Cryptography" PLS Laboratory "Mathematics of Cryptography & Algorithms for Computer Security"

Maria Kurańskaمشاهده پروفایل

مدرس

• Polymer Chemistry
• Green Chemistry
• Bio-based Materials
• +۵ مورد دیگر

Maria Kurańska serves as a Lecturer in the Department of Polymer Chemistry and Technology at the Faculty of Chemical Engineering and Technology, Tadeusz Kościuszko Cracow University of Technology. Her academic career demonstrates continuous progression through doctoral studies and postgraduate environmental specialization, supported by international research collaborations. Educational background includes: MSc Eng. in Plastics Technology (2010) Dr. Eng. in Chemical Technology (2014) Postgraduate studies in Environmental Protection and Engineering (2017) Her research program centers on sustainable polymer development, particularly bio-based polyurethane systems derived from renewable resources like vegetable oils and agricultural waste. Current investigations focus on optimizing foam structures for thermal insulation while maintaining eco-friendly production processes. This work bridges fundamental polymer chemistry with practical applications in construction and environmental protection, emphasizing circular economy principles through material recycling and waste valorization. Publication analysis reveals consistent thematic focus on green chemistry applications, with recent work exploring novel polyol sources from non-edible oils, waste-derived fillers, and circular economy integration. The research demonstrates methodological evolution from basic material synthesis toward complex system optimization and lifecycle analysis. Scientific recognition includes: Multiple doctoral scholarships (2010-2013) International poster awards (Latvia 2012, Hungary 2014) Rector's Team Awards for scientific achievements (2014, 2016) Youngest promoted doctor award (2015) Professor Zbigniew Engel Award for doctoral dissertation (2017) Grant leadership demonstrates significant research capacity, managing multiple EU and national projects focused on bio-polyurethane development. Current projects explore advanced applications including shape-memory biofoams and waste-derived composites. Teaching responsibilities span environmental protection in chemical technology, plastics technology, and polymer laboratories, connecting theoretical knowledge with sustainable practice. International collaborations with Latvian and Argentine institutions enhance the global relevance of her work in renewable material science.

• Experimental psychology
• Educational psychology
• Social psychology
• +۳ مورد دیگر

Kempei Shiina is a Professor at the Faculty of Education and Integrated Arts and Sciences, Waseda University , with a career spanning over three decades. He holds a PhD in Psychology (1994) and a Master of Arts (1983) from Waseda University. Research Focus: Experimental psychology, educational and social psychology, psychometrics, and cognitive modeling. Key Contributions: Historical analysis of rating scales, correlation coefficient anomalies, cursor trajectory-based decision analysis, and computational psychometrics. His recent work explores the historical roots of GPA systems , Jesuit evaluation methods , and the biases in Pearson’s correlation coefficients when applied to categorical data. He has pioneered the use of cursor movement analysis to infer cognitive hesitation and decision-making processes in rating tasks. Scientific Awards: Winner of the 13th Optical Illusion Contest (2021) for the 'Rotating Objects on a Checkerboard Pattern' illusion. His publications and presentations span educational psychology , cognitive science , and statistical history , with over 17 papers and 20 research projects funded by the Japan Society for the Promotion of Science. Teaching: Offers graduate courses in mathematical modeling, educational evaluation, and psychological experimentation at Waseda University. Professional memberships include the Japanese Psychological Association and the Japan Behaviormetrics Society .

Nathaniel Johnstonمشاهده پروفایل

پژوهشگر

• Quantum Information Theory
• Quantum Entanglement
• Matrix Analysis
• +۱۶ مورد دیگر

Nathaniel Johnston is a researcher specializing in quantum information theory, combinatorics, and computational mathematics. He is the creator of QETLAB , a MATLAB toolbox for quantum entanglement, and the founder of ConwayLife.com , a major resource on cellular automata including the comprehensive LifeWiki. He also maintains StatDistributions.com and PlatPrices.com. His research spans: Quantum entanglement and quantum error correction Superpermutations and combinatorics on words Conway’s Game of Life and cellular automata Matrix norms and linear preserver problems Applications of linear algebra to puzzles like Lights Out Geometric optimization and calculus problems He produces educational math videos using Manim, covering advanced topics in an accessible format. His scholarly output includes significant contributions to open problems in mathematics and software tools widely used in the research community. He actively engages with users via GitHub and social media (Bluesky). Notable Projects: QETLAB : A MATLAB toolbox for quantum entanglement, actively developed and cited in research. ConwayLife.com / LifeWiki : The largest encyclopedia of Conway’s Game of Life patterns. StatDistributions.com : A tool for calculating p-values and test statistics. PlatPrices.com : A non-academic site tracking PlayStation game prices and trophies. Scientific Contributions: Disproved the minimal superpermutation conjecture. Developed algorithms for computing hard-to-compute matrix norms. Created accessible explanations of complex topics via video and interactive tools. While his current institutional affiliation is not stated, his body of work, software development, and scholarly communication confirm his status as an active academic researcher in applied and computational mathematics.

Guillaume Rabusseauمشاهده پروفایل

دانشیار

• Machine Learning
• Multilinear Algebra
• Tensor Networks
• +۴ مورد دیگر

Guillaume Rabusseau is an Associate Professor at Mila and the Department of Computer Science and Operations Research (DIRO) at Université de Montréal , holding a Canada CIFAR AI Chair since 2019. His research spans machine learning, theoretical computer science, and multilinear algebra. Education : PhD in Computer Science (2016) from Aix-Marseille Université , MSc in Fundamental Computer Science from AMU, BSc in Computer Science (distance learning) from AMU. Research Interests : Tensor methods for machine learning, spectral learning algorithms, connections between weighted automata, tensor networks, and RNNs, low-rank regression, and nonlinear computational models on structured data. Publication Trends : Recent work focuses on tensor train decomposition, temporal graph benchmarks, quantum-inspired ML, spectral regularization, and formal methods for sequence modeling. Collaborative papers address dynamic graphs, foundational models for molecular learning, and high-order pooling in GNNs. Scientific Awards : Canada CIFAR AI Chair (2019–present, renewed) Advising : Supervises PhD students like Maude Lizaire and Pascal Tikeng Notsawo, and MSc students such as Soroush Omranpour. Past advisees include Andy Huang (now at Oxford) and Tianyu Li (Samsung).

Daniel Alpayمشاهده پروفایل

استاد

• Schur Analysis
• Slice-Hyperholomorphic Functions
• Signal Processing
• +۲۳ مورد دیگر

Dr. Daniel Alpay is a Professor and holder of the Foster G. and Mary McGaw Professorship in Mathematical Sciences at Chapman University. He is affiliated with both Schmid College of Science and Technology and Fowler School of Engineering, contributing to mathematical research and its applications in electrical engineering. His expertise spans Schur Analysis, Slice-Hyperholomorphic Functions, Signal Processing, Linear Systems, Wavelet Filters, and White Noise Space. Dr. Alpay earned his PhD and MSc in Theoretical Mathematics from the Weizmann Institute of Science (Israel) under Prof. Harry Dym (1986, 1980-1986) and an Electrical Engineering degree from École Nationale Supérieure des Télécommunications (France, 1975-1978). His research focuses on infinite-dimensional analysis, hypercomplex structures, and interdisciplinary applications in signal processing and electrical engineering. His recent publications (2024) demonstrate a strong emphasis on Schur Analysis, hyperholomorphic functions, and their applications in stochastic processes, interpolation theory, and superoscillations. These works bridge pure mathematics with engineering, particularly in wavelet filters and linear systems. Dr. Alpay serves as Editor-in-Chief for the journal Complex Analysis and Operator Theory , reflecting his leadership in advancing mathematical research. His work continues to explore connections between abstract mathematical theories and practical engineering problems.

Nicholas Stoneمشاهده پروفایل

استادیار

• Astrophysical Transients
• Tidal Disruption Events
• Accretion Disks
• +۳ مورد دیگر

Nicholas Stone is an Assistant Professor at the University of Wisconsin–Madison, specializing in astrophysical transients, tidal disruption events, and multimessenger astronomy. His research bridges gravitational wave physics, accretion disk dynamics, and galactic nuclei studies. Key Research Areas: Tidal Disruption Events, Gravitational Wave Sources, Accretion Disks, Orbital Dynamics, Multimessenger Astronomy. Recent publications focus on tidal disruption event rates, black hole mergers in AGN, and collapsar disk fragmentation. Collaborative work spans institutions studying X-ray quasi-periodic eruptions and chaotic orbital disruptions. While not explicitly listed, his work implies significant contributions to astrophysics through theoretical modeling and observational data analysis.

Luc Brunمشاهده پروفایل

استاد

• Color Image Segmentation
• Combinatorial Maps
• Graph Metrics
• +۴ مورد دیگر

Luc Brun is a Professor at ENSICAEN (Engineering school of University of Caen Normandy ), affiliated with the Image team at GREYC research laboratory. His research spans multiple domains in Computer Science with focus on Image Processing , Graph Theory , and Machine Learning . Key research areas: Color image quantization, Combinatorial pyramids, Graph edit distance, Graph kernels, Chemoinformatics, Sleep stage classification Academic contributions: 15+ years of teaching in ENSICAEN's Image major, supervision of 13 PhD students His recent publications focus on graph neural networks for biomedical applications (2024-2025), with innovative approaches to SPD matrix processing and graph pooling . Earlier work established foundational methods in color image segmentation (2000-2003) and combinatorial map representations (1999-2003). Scientific awards and honors: Co-inventor of audio fingerprinting technology (2006 patent) Key contributor to combinatorial pyramid frameworks Developer of segmentation software DesCartes Active participant in IAPR-TC15 committee Supervised researchers now hold positions across academia (Assistant Professor at University of Salerno, Post-doc at Baclesse Hospital) and industry (Research Engineer at NeuroRx, Ingénieur at IT Link). Current projects include differentiable graph edit distance and time-frequency EEG analysis for sleep monitoring.

Matthieu Becuweمشاهده پروفایل

استاد

• Energy Storage
• Organic Materials
• Hybrid Materials
• +۴ مورد دیگر

Matthieu Becuwe is a Professor at the University of Picardie Jules Verne, affiliated with the Laboratory of Reactivity and Chemistry of Solids (LRCS, UMR CNRS 7314) and serving as Director of the Picardy Institute of Chemistry (FR 3085). His research focuses on designing functional molecular and hybrid materials for energy storage applications, particularly in lithium-ion batteries and emerging all-organic ionic systems. Research Interests : Electrochemical performance optimization, molecular engineering of organic electrode materials, solid-state electrolytes, and environmentally sustainable battery technologies. Projects : Leads ANR PRC DEOSS and COMETS projects; contributes to Horizon Europe’s PSIONIC and France 2030-PEPR initiatives like SONIC and DISCOVERY. Expertise : Materials synthesis (silica matrices, hybrid nanomaterials), electrochemical characterization (GCPL, CV), and advanced analytical techniques (solid-state NMR, X-ray diffraction, electron microscopy).

Michael Strubeمشاهده پروفایل

استاد

• Natural Language Processing
• Computational Linguistics
• Semantics and Discourse Pragmatics
• +۷ مورد دیگر

Michael Strube is an Honorary Professor at the Department of Computational Linguistics at Heidelberg University and leads the Natural Language Processing (NLP) Group at HITS (Heidelberg Institute for Theoretical Studies) in Germany. He has been with HITS (previously EML Research and European Media Laboratory) since 2003 and became an Honorary Professor at Heidelberg University in 2010. He is also a Fellow of the Association for Computational Linguistics (2019). Dr. Strube received his PhD from the Computational Linguistics Department at the University of Freiburg in December 1996 under the supervision of Udo Hahn. Between 1997 and 1999, he was a postdoctoral fellow at the Institute for Research in Cognitive Science at the University of Pennsylvania, Philadelphia. Michael Strube's research focuses on semantics and discourse pragmatics, graph-based methods for text representation and analysis, extraction of world knowledge from Wikipedia for computational linguistics, and development of methods to synchronize multilingual content. His work spans coreference resolution, discourse processing, text summarization, entity linking, and natural language generation. He has made significant contributions to coherence modeling, anaphora resolution, and the application of geometric deep learning in NLP. His recent publications demonstrate strong trends in discourse processing, coreference resolution, and the application of geometric approaches to NLP problems. Strube has pioneered work in hyperbolic space for entity typing and graph embeddings, while maintaining his foundational work in discourse and coherence. His research bridges theoretical linguistics with practical NLP applications across multiple languages. Dr. Strube has received several prestigious awards, including: Fellow of the Association for Computational Linguistics (2019) Best Paper Award for "Fine-grained entity typing in hyperbolic space" (2019) Honorable Mention for the IJCAI-JAIR best paper prize 2010 for "Knowledge Derived from Wikipedia for Computing Semantic Relatedness" Professor Strube has advised numerous PhD students who have gone on to successful careers in academia and industry. His current PhD students include Yi Fan, Wei Liu, Haixia Chai, Mehwish Fatima, and Sungho Jeon, working on topics such as discourse structure, discourse relations, coreference resolution, and cross-lingual summarization. His former students include Federico Lopez, Benjamin Heinzerling, Mohsen Mesgar, and Nafise Moosavi, who now hold positions at institutions like Argo AI, RIKEN, Bosch Center for AI, and the University of Sheffield. As group leader of the NLP Group at HITS, Strube oversees a team focused on advancing natural language processing through research in discourse analysis, coreference resolution, text generation, and knowledge extraction. The group has been involved in numerous collaborative projects and has made significant contributions to the field through publications, shared tasks, and community building via workshops and conferences.

Bogdan Stefanskiمشاهده پروفایل

استاد

• String Theory
• Quantum Field Theory
• AdS/CFT Correspondence
• +۵ مورد دیگر

Dr. Bogdan Stefanski is a Professor of Theoretical Physics and Director of Research at the Centre for Mathematical Science, City, University of London. With a career spanning institutions like the Max Planck Institute, Spinoza Institute, Imperial College London, and Massachusetts Institute of Technology, he has established himself as a leading expert in string theory and integrable systems. PhD in Mathematics, University of Cambridge (2000) Part III Mathematics, University of Cambridge (1996) BSc (Hons) in Mathematics & Physics, University of Natal (1995) His research focuses on the intersection of string theory and quantum field theory, particularly exploring the AdS/CFT correspondence , integrability in superstring sigma models , and the mathematical structures underlying Calabi-Yau manifolds and K-theory . His work addresses fundamental questions about how supersymmetric gauge theories emerge from 10-dimensional string constructions , with implications for quantum gravity and non-perturbative effects. Recent publications analyze the low-energy limits of AdS3/CFT2 , dressing factors in integrable systems , and quantum spectral curves . These papers often involve collaborations with researchers like Olof Ohlsson Sax and Alessandro Torrielli, appearing in venues such as the Journal of High Energy Physics and Journal of Physics A. EPSRC Advanced Research Fellow Marie Curie Intra-European and Outgoing Fellow Foundation for Fundamental Research on Matter Fellow Bogdan Stefanski's work bridges formal string theory with mathematical physics, leveraging advanced techniques in Yangian symmetry , boundary superstring field theory , and non-linear sigma models to unravel the deep connections between gravity, gauge theory, and quantum information.